Determining the underlying regulatory mechanism of genetic networks is one of the central challenges of computational biology. Numerous methods have been developed and applied to the important but complex task of reve...
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ISBN:
(纸本)9783540738466
Determining the underlying regulatory mechanism of genetic networks is one of the central challenges of computational biology. Numerous methods have been developed and applied to the important but complex task of reverse engineering regulatory networks from high-throughput gene expression data. However, many challenges remain. In this paper, we are interested in learning rules that will reveal the causal genes for the expression variation from various relational data sources in addition to gene expression data. Following our previous work where we showed that time series gene expression data could potentially uncover causal effects, we describe an application of an inductive logic programming (ILP) system, to the task of identifying important regulatory relationships from discretized time series gene expression data, protein-protein interaction, protein phosphorylation and transcription factor data about the organism. Specifically, we learn rules for predicting gene expression levels at the next time step based on the available relational data and then generalize the learned theory to visualize a pruned network of important interactions. We evaluate and present experimental results on microarray experiments from Gasch et al on Saccharomyces cerevisiae.
logic programming (LP) is a subcategory of declarative programming that is considered to be relatively simple for non-programmers. LP developers focus on describing facts and rules of a logical derivation, and do not ...
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ISBN:
(纸本)9781450386890
logic programming (LP) is a subcategory of declarative programming that is considered to be relatively simple for non-programmers. LP developers focus on describing facts and rules of a logical derivation, and do not need to think about the algorithms actually implementing the derivation. Secure multiparty computation (MPC) is a cryptographic technology that allows to perform computation on private data without actually seeing the data. In this paper, we bring together the notions of MPC and LP, allowing users to write privacy-preserving applications in logic programming language.
The question of the termination of logic programming computations is studied from a semantical point of view. To every program are associated two first order formulas. Their valid consequences are respectively the fin...
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logic programming, a class of programming languages based on first-order logic, provides simple and efficient tools for goal-oriented proof-search. logic programming supports recursive computations, and some logic pro...
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ISBN:
(纸本)9783642177958
logic programming, a class of programming languages based on first-order logic, provides simple and efficient tools for goal-oriented proof-search. logic programming supports recursive computations, and some logic programs resemble the inductive or coinductive definitions written in functional programming languages. In this paper, we give a coalgebraic semantics to logic programming. We show that ground logic programs can be modelled by either P-f P-f-coalgebras or P-f List-coalgebras on Set. We analyse different kinds of derivation strategies and derivation trees (proof-trees, SLD-trees, and-or parallel trees) used in logic programming, and show how they can be modelled coalgebraically.
In this paper we present a new static data type inference algorithm for logic programming. Without the need for declaring types for predicates, our algorithm is able to automatically assign types to predicates which, ...
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ISBN:
(数字)9783030988692
ISBN:
(纸本)9783030988692;9783030988685
In this paper we present a new static data type inference algorithm for logic programming. Without the need for declaring types for predicates, our algorithm is able to automatically assign types to predicates which, in most cases, correspond to the data types processed by their intended meaning. The algorithm is also able to infer types given data type definitions similar to data definitions in Haskell and, in this case, the inferred types are more informative, in general. We present the type inference algorithm, prove it is decidable and sound with respect to a type system, and, finally, we evaluate our approach on example programs that deal with different data structures.
Navigation and interaction patterns of Web users can be relatively complex, especially for sites with interactive applications that support user sessions and profiles. We describe such a case for an interactive virtua...
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ISBN:
(纸本)076952415X
Navigation and interaction patterns of Web users can be relatively complex, especially for sites with interactive applications that support user sessions and profiles. We describe such a case for an interactive virtual garment dressing room. The application is distributed over many web sites, supports personnalization and user profiles, and the notion of a multi-site user session. It has its own data logging system that generates approximately 5GB of complex dataper month. The analysis of those logs requires more sophisticated processing than is typically done using a relational language. Even the use of procedural languages and DBMS can prove tedious and inefficient. We show an approach to the analysis of complex log data based on a parallel stream processing architecture and the use of specialized languages, namely a grammatical parser and a logic programming module, that offers an efficient, flexible, and powerful solution.
Introducing fuzzy predicates in inductive logic programming may serve two different purposes : getting more expressivity by learning fuzzy rules, or allowing for more adaptability when learning classical rules. On the...
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ISBN:
(纸本)0780383532
Introducing fuzzy predicates in inductive logic programming may serve two different purposes : getting more expressivity by learning fuzzy rules, or allowing for more adaptability when learning classical rules. On the one hand, we can thus learn gradual and certainty rules, which have an increased expressive power and have no simple crisp counterpart. On the other hand, fuzzy predicates in rules can be used for dicretization when the database contains numerical attributes. In this case the fuzzy counterparts of crisp rules allow us to check the meaningfulness and the accuracy of the crisp rules. In this paper we formally describe the computation of the confidence degrees for each type of rules with fuzzy predicates. Next, we discuss the interest and the application domain of each kind of rules with fuzzy predicates.
Inductive logic programming (ILP) systems have been largely applied to classification problems with a considerable success. The use of ILP systems in problems requiring numerical reasoning capabilities has been far le...
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ISBN:
(纸本)3540238069
Inductive logic programming (ILP) systems have been largely applied to classification problems with a considerable success. The use of ILP systems in problems requiring numerical reasoning capabilities has been far less successful. Current systems have very limited numerical reasoning capabilities, which limits the range of domains where the ILP paradigm may be applied. This paper proposes improvements in numerical reasoning capabilities of ILP systems. It proposes the use of statistical-based techniques like Model Validation and Model Selection to improve noise handling and it introduces a new search stopping criterium based on the PAG method to evaluate learning performance. We have found these extensions essential to improve on results mer statistical-based algorithms for time series forecasting used in the empirical evaluation study.
logic programming (LP) has been successfully applied to solve many problems in Artificial Intelligence and many other areas. However, LP is unable to deal with uncertain, imprecise or vague information. On the other h...
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ISBN:
(纸本)0780344537
logic programming (LP) has been successfully applied to solve many problems in Artificial Intelligence and many other areas. However, LP is unable to deal with uncertain, imprecise or vague information. On the other hand, Fuzzy Sets and Fuzzy logic have demonstrated their applicability in dealing with uncertainty, and have motivated the research on extending classic LP to add fuzzy reasoning. However, a full fledged implementation of a fuzzy logic programming language universally accepted and/or in production does not exists yet. There are many reasons for this, and we present some of them in this paper. The aim of this paper is to briefly survey some of the major design problems we faced in implementing a fuzzy version of a Prolog-like logic programming language.
We present a new declarative compilation of logic programs with constraints into variable-free relational theories which are then executed by rewriting. This translation provides an algebraic formulation of the abstra...
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ISBN:
(纸本)9783319178226;9783319178219
We present a new declarative compilation of logic programs with constraints into variable-free relational theories which are then executed by rewriting. This translation provides an algebraic formulation of the abstract syntax of logic programs. Management of logic variables, unification, and renaming apart is completely elided in favor of algebraic manipulation of variable-free relation expressions. We prove the translation is sound, and the rewriting system complete with respect to traditional SLD semantics.
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